PROJECT SUMMARY/ABSTRACT Although sleep is generally believed to be essential for survival, the neuronal mechanisms by which it affects brain function are largely unknown. Does sleep constitute a passive state in which the brain is `quiet' or does it play an important role for network coding and behavior in subsequent tasks? Even though the functional significance of sleep is not well understood, the available data suggest that significant improvements in learning and memory are found even after brief naps. A critical issue for understanding sleep function is whether and how it impacts the accuracy of neuronal network computations to improve behavioral performance. We will address these issues for the first time by examining whether brief sleep (20 min of rest) influences visual perceptual performance and the coding of visual information across neuronal populations. We propose to use multiple-electrode recording simultaneously in two visual cortical areas (V1 and V4) of awake behaving monkey to examine the dynamics and coding in neuronal populations before, during, and after sleep, and their impact on perceptual performance. Aim 1 will examine how sensory experience changes the structure of network activity during rest by determining (i) how task exposure modifies the distribution of neuronal correlations across networks during rest, and (ii) if cells that are coactivated during stimulus exposure are more likely to be reactivated during subsequent rest. Aim 2 will examine whether brief sleep influences subsequent stimulus coding by individual neurons and networks by determining (i) whether single neuron discrimination performance is improved after rest, and (ii) whether and how correlated activity across the network is modified after rest. By decoding the population response we will determine (iii) whether neuronal populations encode more information after rest, and (iv) whether and how rest changes the synchrony between individual neurons and local population activity. Aim 3 will examine whether rest influences the relationship between neuronal and behavioral performance by determining (i) whether behavioral performance is improved after rest, (ii) whether the post-sleep neuronal and behavioral performance are correlated, (iii) whether LFP activity and spike-LFP synchronization during sleep are correlated with post-rest behavioral performance, (iv) whether there is a relationship between the amount of rest and the improvement in network and behavioral performance. Our research has the potential to advance our understanding of the neural mechanisms underlying rest and sleep and thus provide future solutions to ameliorate the detrimental effects of sleep disorder on cognitive performance, including practical applications for non-invasive neuronal prosthetic devices.